Databricks is present in 7 markets with 7 products. Databricks has 443 reviews with an overall average rating of 4.7.
Analytics Query Accelerators
Analytics query accelerators provide SQL or SQL-like query support on a broad range of data sources. They are most frequently used as a means of providing interactive and production-optimized delivery on semantically flexible data stores that do not inherently have the capabilities to provide sufficient performance or ease of use on their own. Commonly used in conjunction with data lakes, they aim to support BI dashboards, interactive query capabilities, data modeling and other analytics use cases.
Databricks has 1 product in Analytics Query Accelerators market
Analytics and Business Intelligence Platforms
Analytics and business intelligence platforms — enabled by IT and augmented by AI — empower users to model, analyze and share data. Analytics and business intelligence (ABI) platforms enable organizations to understand their data. For example, what are the dimensions of their data — such as product, customer, time, and geography? People need to be able to ask questions about their data (e.g., which customers are likely to churn? Which salespeople are not reaching their quotas?). They need to be able to create measures from their data, such as on-time delivery, accidents in the workplace and customer or employee satisfaction. Organizations need to blend modeled and nonmodeled data to create new data pipelines that can be explored to find anomalies and other insights. ABI platforms make all of this possible.
Databricks has 1 product in Analytics and Business Intelligence Platforms market
Cloud Database Management Systems
Gartner defines the market for cloud database management systems (DBMSs) as the market for software products that store and manipulate data and that are primarily delivered as software as a service (SaaS) in the cloud. Cloud DBMSs may optionally be capable of running on-premises, or in hybrid, multicloud or intercloud configurations. They can be used for transactional work and/or analytical work. They may have features that enable them to participate in a wider data ecosystem. Must-have capabilities for this market include: Availability as SaaS on provider-managed public or private cloud systems; Management of data within cloud storage — that is, cloud DBMSs are not hosted in infrastructure as a service (IaaS), such as in a virtual machine or a container managed by the customer.
Databricks has 1 product in Cloud Database Management Systems market
Data Science and Machine Learning Platforms
Gartner defines a data science and machine learning platform as an integrated set of code-based libraries and low-code tooling that support the independent use by, and collaboration between, data scientists and their business and IT counterparts through all stages of the data science life cycle. These stages include business understanding, data access and preparation, experimentation and model creation, and sharing of insights. They also support machine learning engineering workflows including creation of data, feature, deployment and testing pipelines. The platforms are provided via desktop client or browser with supporting compute instances and/or as a fully managed cloud offering. Data science and machine learning (DSML) platforms are designed to allow a broad range of users to develop and apply a comprehensive set of predictive and prescriptive analytical techniques. Leveraging data from distributed sources, cutting-edge user experience, and native machine learning and generative AI (GenAI) capabilities, these platforms help to augment and automate decision making across an enterprise. They provide a range of proprietary and open-source tools to enable data scientists and domain experts to find patterns in data that can be used to forecast financial metrics, understand customer behavior, predict supply and demand, and many other use cases. Models can be built on all types of data, including tabular, images, video and text for applications that require computer vision or natural language processing.
Databricks has 1 product in Data Science and Machine Learning Platforms market
DataOps Tools
Gartner defines DataOps as the collaborative data management practice focusing on improving communication, continuous integration, automation, observability and operations of data flows between data managers, data consumers, and their teams across the organization. DataOps tools connect and orchestrate data pipelines across heterogeneous systems. Data and analytics leaders are the buyers in this emerging market. The primary audience for DataOps tools is “data manager” personas like, data engineers, data integration developers, operations/incident analysts, database administrators and data architects. The secondary audience is “data consumer” personas like business analysts, business intelligence developers, data scientists and citizen roles (departmental users who are domain experts, but less technical).
Databricks has 1 product in DataOps Tools market
Generative AI Engineering
Generative AI (GenAI) engineering refers to the field of engineering that focuses on the development, implementation and optimization of generative AI models. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. By developing GenAI models, engineers can create new and innovative ways to generate content. The vendors in this segment are made up by incumbent and startup vendors covering full-model life cycle management, specifically adjusted to and catering to development, refinement and deployment of generative models (e.g., LLMs) and other GenAI artifacts in production applications. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Databricks has 1 product in Generative AI Engineering market
Generative AI Model Providers
Generative AI (GenAI) model providers focus on developing and providing generative AI technologies and make them available to other developers, businesses and general public through APIs or commercial licenses. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. This layer of vendors offers access to commercial or open-source foundation models such as LLMs and other types of generative algorithms (such as GANs, genetic/evolutionary algorithms or simulations). These models can be provided for developers to embed into their applications or be used as base models for fine-tuning customized models for their software offerings or internal enterprise use cases. This helps businesses gain the benefits of advanced generative AI technologies while avoiding the high costs, expertise requirements and time needed to develop these technologies in-house. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.
Databricks has 1 product in Generative AI Model Providers market